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import cv2import mathimport timeimport argparsedef getFaceBox(net, frame,conf_threshold = 0.75):    frameOpencvDnn = frame.copy()    frameHeight = frameOpencvDnn.shape[0]    frameWidth = frameOpencvDnn.shape[1]    blob = cv2.dnn.blobFromImage(frameOpencvDnn,1.0,(300,300),[104, 117, 123], True, False)    net.setInput(blob)    detections = net.forward()    bboxes = []    for i in range(detections.shape[2]):        confidence = detections[0,0,i,2]        if confidence > conf_threshold:            x1 = int(detections[0,0,i,3]* frameWidth)            y1 = int(detections[0,0,i,4]* frameHeight)            x2 = int(detections[0,0,i,5]* frameWidth)            y2 = int(detections[0,0,i,6]* frameHeight)            bboxes.append([x1,y1,x2,y2])            cv2.rectangle(frameOpencvDnn,(x1,y1),(x2,y2),(0,255,0),int(round(frameHeight/150)),8)    return frameOpencvDnn , bboxesfaceProto = "opencv_face_detector.pbtxt"faceModel = "opencv_face_detector_uint8.pb"ageProto = "age_deploy.prototxt"ageModel = "age_net.caffemodel"genderProto = "gender_deploy.prototxt"genderModel = "gender_net.caffemodel"MODEL_MEAN_VALUES = (78.4263377603, 87.7689143744, 114.895847746)ageList = ['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']genderList = ['Male', 'Female']#load the networkageNet = cv2.dnn.readNet(ageModel,ageProto)genderNet = cv2.dnn.readNet(genderModel, genderProto)faceNet = cv2.dnn.readNet(faceModel, faceProto)cap = cv2.VideoCapture(0)padding = 20while cv2.waitKey(1) < 0:    #read frame    t = time.time()    hasFrame , frame = cap.read()    if not hasFrame:        cv2.waitKey()        break    #creating a smaller frame for better optimization    small_frame = cv2.resize(frame,(0,0),fx = 0.5,fy = 0.5)    frameFace ,bboxes = getFaceBox(faceNet,small_frame)    if not bboxes:        print("No face Detected, Checking next frame")        continue    for bbox in bboxes:        face = small_frame[max(0,bbox[1]-padding):min(bbox[3]+padding,frame.shape[0]-1),                max(0,bbox[0]-padding):min(bbox[2]+padding, frame.shape[1]-1)]        blob = cv2.dnn.blobFromImage(face, 1.0, (227, 227), MODEL_MEAN_VALUES, swapRB=False)        genderNet.setInput(blob)        genderPreds = genderNet.forward()        gender = genderList[genderPreds[0].argmax()]        print("Gender : {}, conf = {:.3f}".format(gender, genderPreds[0].max()))        ageNet.setInput(blob)        agePreds = ageNet.forward()        age = ageList[agePreds[0].argmax()]        print("Age Output : {}".format(agePreds))        print("Age : {}, conf = {:.3f}".format(age, agePreds[0].max()))        label = "{},{}".format(gender, age)        cv2.putText(frameFace, label, (bbox[0], bbox[1]-10), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 255), 2, cv2.LINE_AA)        cv2.imshow("Age Gender Demo", frameFace)    print("time : {:.3f}".format(time.time() - t))